Postdoc: Multimodal AI for Predictive Biology

Johnson Johnson; Belgique; Sur place; EUR 53 000 - 66 000; Plein temps

Résumé du poste

Johnson & Johnson Innovative Medicine seeks a Postdoctoral Scientist to advance AI/ML modeling for predictive biology, joining the DDSAI group for a two-year fixed-term position. Location options include Cambridge, MA; Spring House, Beerse, Belgium; or Madrid, Spain with no full remote option.

The successful candidate will develop multimodal representations across imaging, omics, and phenomics data to drive drug discovery insights and publish findings in top venues.

Qualifications

• PhD completed within the last 3 years or to be completed within the next 6 months.
• Strong expertise in AI/ML for biological applications with analytical skills in representation learning and multimodal integration.
• Experience developing foundation models and multimodal modeling of biological data.

Responsabilités

• Conceive, design, develop, implement and validate AI/ML solutions for drug discovery using multimodal data of perturbed cells.
• Analyze and extract novel biological insights from large high-dimensional data (imaging, phenomics, transcriptomics, proteomics).
• Develop and evaluate computer vision solutions to quantify heterogeneity of perturbed cells.
• Collaborate with cross-functional teams to advance algorithms and product development.
• Communicate complex methodologies and present findings to diverse audiences.
• Maintain code repositories and document processes.
• Draft manuscripts and disseminate findings in peer-reviewed venues.

Connaissances

AI/ML for biology

Multimodal learning

Computational biology

Imaging microscopy

Formation

PhD in EE / BME / CS / Applied Math

Description du poste

Johnson & Johnson Innovative Medicine seeks a Postdoctoral Scientist to advance AI/ML modeling for predictive biology, joining the DDSAI group for a two-year fixed-term position. Location options include Cambridge, MA; Spring House, Beerse, Belgium; or Madrid, Spain with no full remote option.

The successful candidate will develop multimodal representations across imaging, omics, and phenomics data to drive drug discovery insights and publish findings in top venues.